Literature DB >> 19282235

Modeling QTL for complex traits: detection and context for plant breeding.

Mark Cooper1, Fred A van Eeuwijk, Graeme L Hammer, Dean W Podlich, Carlos Messina.   

Abstract

The genetic architecture of a trait is defined by the set of genes contributing to genetic variation within a reference population of genotypes together with information on their location in the genome and the effects of their alleles on traits, including intra-locus and inter-locus interactions, environmental dependencies, and pleiotropy. Accumulated evidence from trait mapping studies emphasizes that plant breeders work within a trait genetic complexity continuum. Some traits show a relatively simple genetic architecture while others, such as grain yield, have a complex architecture. An important advance is that we now have empirical genetic models of trait genetic architecture obtained from mapping studies (multi-QTL models including various genetic effects that may vary in relation to environmental factors) to ground theoretical investigations on the merits of alternative breeding strategies. Such theoretical studies indicate that as the genetic complexity of traits increases the opportunities for realizing benefits from molecular enhanced breeding strategies increase. To realize these potential benefits and enable the plant breeder to increase rate of genetic gain for complex traits it is anticipated that the empirical genetic models of trait genetic architecture used for predicting trait variation will need to incorporate the effects of genetic interactions and be interpreted within a genotype-environment-management framework for the target agricultural production system.

Mesh:

Year:  2009        PMID: 19282235     DOI: 10.1016/j.pbi.2009.01.006

Source DB:  PubMed          Journal:  Curr Opin Plant Biol        ISSN: 1369-5266            Impact factor:   7.834


  24 in total

1.  Using probe genotypes to dissect QTL × environment interactions for grain yield components in winter wheat.

Authors:  Bing Song Zheng; Jacques Le Gouis; Martine Leflon; Wen Ying Rong; Anne Laperche; Maryse Brancourt-Hulmel
Journal:  Theor Appl Genet       Date:  2010-08-10       Impact factor: 5.699

Review 2.  Phenomics: the next challenge.

Authors:  David Houle; Diddahally R Govindaraju; Stig Omholt
Journal:  Nat Rev Genet       Date:  2010-12       Impact factor: 53.242

3.  Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.

Authors:  D Wang; I Salah El-Basyoni; P Stephen Baenziger; J Crossa; K M Eskridge; I Dweikat
Journal:  Heredity (Edinb)       Date:  2012-08-15       Impact factor: 3.821

4.  Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

Authors:  Karine Chenu; Scott C Chapman; François Tardieu; Greg McLean; Claude Welcker; Graeme L Hammer
Journal:  Genetics       Date:  2009-09-28       Impact factor: 4.562

5.  Genome-wide association mapping of yield and yield components of spring wheat under contrasting moisture regimes.

Authors:  Erena A Edae; Patrick F Byrne; Scott D Haley; Marta S Lopes; Matthew P Reynolds
Journal:  Theor Appl Genet       Date:  2014-01-10       Impact factor: 5.699

6.  Simulating the impact of genetic diversity of Medicago truncatula on germination and emergence using a crop emergence model for ideotype breeding.

Authors:  S Brunel-Muguet; J-N Aubertot; C Dürr
Journal:  Ann Bot       Date:  2011-04-18       Impact factor: 4.357

Review 7.  Accelerating crop genetic gains with genomic selection.

Authors:  Kai Peter Voss-Fels; Mark Cooper; Ben John Hayes
Journal:  Theor Appl Genet       Date:  2018-12-19       Impact factor: 5.699

8.  Dissecting quantitative trait loci for boron efficiency across multiple environments in Brassica napus.

Authors:  Zunkang Zhao; Likun Wu; Fuzhao Nian; Guangda Ding; Taoxiong Shi; Didi Zhang; Lei Shi; Fangsen Xu; Jinling Meng
Journal:  PLoS One       Date:  2012-09-24       Impact factor: 3.240

9.  Phenotyping for drought tolerance of crops in the genomics era.

Authors:  Roberto Tuberosa
Journal:  Front Physiol       Date:  2012-09-19       Impact factor: 4.566

10.  Disentangling the intertwined genetic bases of root and shoot growth in Arabidopsis.

Authors:  Marie Bouteillé; Gaëlle Rolland; Crispulo Balsera; Olivier Loudet; Bertrand Muller
Journal:  PLoS One       Date:  2012-02-24       Impact factor: 3.240

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